Publication
Predicting the Total Costs of Production Factors on Farms in the European Union
| Summary: | The dynamics of the agricultural sector depend on the performance of the farms and their respective profitability. The cost control in the farms is particularly important, considering the reduced profit margins in agriculture. In fact, in some contexts, the level of farm costs is very similar to the amounts of income, calling, in many cases, for financial support for the farmers, justified by the need to guarantee food security and social and environmental sustainability. In this framework, contributions that support policymakers and farmers to make decisions that promote farm cost reduction are fundamental. Considering this scenario, this study intends to consider machine learning approaches and data from the European databases to identify the most adjusted approaches to predict the total costs in the farms. This study brought relevant outputs for the design of adjusted measures, plans and instruments for the European Union agriculture and respective processes and activities. |
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| Main Authors: | Martinho, Vítor |
| Subject: | Artificial intelligence Adjusted models and predictors Agriculture |
| Year: | 2024 |
| Country: | Portugal |
| Document type: | book part |
| Access type: | restricted access |
| Associated institution: | Instituto Politécnico de Viseu |
| Language: | English |
| Origin: | Repositório Científico do Instituto Politécnico de Viseu |
| Summary: | The dynamics of the agricultural sector depend on the performance of the farms and their respective profitability. The cost control in the farms is particularly important, considering the reduced profit margins in agriculture. In fact, in some contexts, the level of farm costs is very similar to the amounts of income, calling, in many cases, for financial support for the farmers, justified by the need to guarantee food security and social and environmental sustainability. In this framework, contributions that support policymakers and farmers to make decisions that promote farm cost reduction are fundamental. Considering this scenario, this study intends to consider machine learning approaches and data from the European databases to identify the most adjusted approaches to predict the total costs in the farms. This study brought relevant outputs for the design of adjusted measures, plans and instruments for the European Union agriculture and respective processes and activities. |
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